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Neural mass model based on single cell dynamics to model pathophysiology (Zandt et al 2014)
 
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Model Information
Model File
Citations
Accession:
155130
The model code as described in "A neural mass model based on single cell dynamics to model pathophysiology, Zandt et al. 2014, Journal of Computational Neuroscience" A Neural mass model (NMM) derived from single cell dynamics in a bottom up approach. Mean and standard deviation of the firing rates in the populations are calculated. The sigmoid is derived from the single cell FI-curve, allowing for easy implementation of pathological conditions. NMM is compared with a detailed spiking network model consisting of HH neurons. NMM code in Matlab. The network model is simulated using Norns (ModelDB # 154739)
Reference:
1 .
Zandt BJ, Visser S, van Putten MJ, Ten Haken B (2014) A neural mass model based on single cell dynamics to model pathophysiology.
J Comput Neurosci
37
:549-68
[
PubMed
]
Model Information
(Click on a link to find other models with that property)
Model Type:
Realistic Network;
Neural mass;
Brain Region(s)/Organism:
Cell Type(s):
Hodgkin-Huxley neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:
C or C++ program;
MATLAB;
Brian;
Python;
Norns - Neural Net Studio;
Model Concept(s):
Simplified Models;
Methods;
Pathophysiology;
Connectivity matrix;
Brain Rhythms;
Implementer(s):
Zandt, Bas-Jan [Bas-Jan.Zandt at biomed.uib.no];
Download the displayed file
/
ZandtEtAl2014
network_and_NMM
Skuld_2_2
Urd_v1_2
VerdandiLite_v1_0
gF_curve.mat
*
Other models using gF_curve.mat:
Neural mass model based on single cell dynamics to model pathophysiology (Zandt et al 2014)
Neural mass model based on single cell dynamics to model pathophysiology (Zandt et al 2014)
meanfieldapprox.m
*
Other models using meanfieldapprox.m:
Neural mass model based on single cell dynamics to model pathophysiology (Zandt et al 2014)
myfour.m
myifour.m
parameters_meanfield.m
run_meanfieldapprox_makefigures.m
URD_2populations_limitcycle.m
URD_determine_gFcurve.m
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